Abstract: Embodiments relate to systems and methods for the delivery of user-controlled resources in cloud environments via a resource specification language wrapper. In embodiments, the user of a client machine may wish to contribute resources from that machine to a cloud-based network via a network connection over a limited or defined period. To expose the user-controlled resources to one or more clouds for use the user may transmit a contribution request encoding the user-controlled resources in a specification language wrapper, such as an XML (extensible markup language) wrapper. The specification language wrapper can embed the set of user-controlled resources, such as processor time, memory, and/or other resources, in an XML or other format to transmit to a marketplace engine which can place the set of user-controlled resources into a resource pool, for selection by marketplace clouds. The specification language wrapper can indicate access controls or restrictions on the contributed resources.

Abstract: A system and method include determining, by a processing device, a first duration of usage of a hardware resource on which a virtual machine is instantiated in a cloud, determining, by the processing device from the virtual machine on the cloud, a second duration of usage of a software resource that is utilized by a user on the virtual machine, the software resource comprising at least part of an operating system, and calculating, by the processing device, a usage of the cloud by the user in view of the first duration and the second duration.

Abstract: A metering tool can monitor the software resources of the cloud to meter the software utilization of the cloud. The metering tool can cooperate and communicate with a cloud management system to determine the software resources utilized by processes instantiated in the cloud and to track the duration of the utilization. The metering tool can store the tracked utilization in a record.

Abstract: Embodiments relate to systems and methods for identifying usage histories and end users that may benefit from being redeployed to a new cloud-based network. In particular, a new cloud can receive usage histories corresponding to end user usage in a respective set of other pre-existing clouds. In embodiments, the new cloud can determine whether the new cloud provides sufficient resources to properly host each end user recorded in the usage histories. Further, the new cloud can determine whether there is a cost benefit or other advantage for a user to move to the new cloud. In embodiments, a deployment recommendation may be sent to an administrator of the cloud associated with the desirable usage history.

Abstract: Embodiments relate to systems and methods for identifying usage histories for producing optimized utilization in a cloud-based network. In particular, a target cloud can receive usage histories corresponding to end user usage in a respective set of other clouds. In embodiments, the target cloud can simulate an execution of the usage histories on resources in the target cloud to generate a set of utilization ratios. Further, the target cloud can determine a desirable usage history from the set of utilization ratios based on highly optimized resource usage within the target cloud. In embodiments, an administrator of the target cloud can provide a deployment recommendation to an administrator of the cloud associated with the desirable usage history.

Abstract: Embodiments relate to systems and methods for migrating software modules into one or more target clouds. The systems and methods can analyze system data to determine software modules supported by the system, and target cloud data to determine which target clouds have a capacity to support a migration of the software modules. In embodiments, benefits of migrating any or all of the software modules to the target clouds can be determined. Based on the benefits, the software modules of the system can be segmented and migrated into systems associated with the multiple target clouds.

Abstract: Embodiments relate to systems and methods for managing a software subscription between an independent software vendor (ISV) and a cloud network provider. In embodiments, the software subscription can be a Software as a Service (SaaS) agreement whereby an amount of resources of the cloud network to be operated by end users can be specified. In embodiments, a resource tracking module associated with the cloud network can track the actual amount of resources operated by the end users in executing applications associated with the ISV. The resource tracking module can compare the actual amount to the amount specified in the SaaS, and adjust the resources of the cloud network accordingly. In embodiments, the SaaS can be updated based on the adjustment.

Abstract: Embodiments relate to systems and methods for exporting usage history data as input to a management platform of a target cloud-based network. A usage export service can be abstracted and provided external to a host cloud-based network, which can capture the usage history of software or resources by one or more users in the host cloud-based network. Those user(s) or others may wish to export some or all of the usage history to a target cloud or clouds, to perform management or configuration actions in the target cloud(s). The selective subset of the usage history can be transmitted to the cloud management system of the target cloud-based network. The selective subset can be used for management actions in the target cloud(s), such as for instance, to instantiate or configure a set of virtual machines for failover or re-clouding purposes, or to aggregate usage history from the host and target cloud(s).

Abstract: Cloud resource provisioning is described. A cloud resource provisioning method may include obtaining cloud resource usage data by a process, wherein the cloud resource usage data identifies a cloud resource consumed by the process and a usage level associated with the cloud resource. The method may also include assigning an importance indicator to the cloud resource, and identifying a recommended cloud resource having available capacity with respect to the usage level in view of the importance indicator.

Abstract: A decision system and methods for providing customized deployment architectures that take into account the importance of various cloud resources. The decision system can monitor the applications and processes executed in the cloud, and collect utilization information identifying the cloud resources used, the amount of usage, and trends in usage. Resource importance data can then be obtained from the utilization information and/or from other sources, such as a system user. The decision system can then generate customized deployment architectures based on the collected utilization information and the resource importance data.

Abstract: A software provider system can provide and price software infrastructure for a cloud to a cloud provider based on expected utilization and actual utilization of the cloud. The software provider system can provide the software infrastructure of the cloud and technical support for the software infrastructure under a varying price structure which is dependent on the expected utilization and the actual utilization of the software infrastructure. The software provider system can determine the initial price of the software infrastructure based on the expected utilization of the cloud and a purpose of the cloud. The software provider system can monitor the actual utilization of the software infrastructure, over time, in order to modify the initial price based on the actual utilization of the software infrastructure.

Abstract: A matching system can provide matching services to users of cloud computing environments. The matching system can receive user requests for sets of services. Once received, the matching system can collect information about available cloud appliances. The matching system can match the cloud appliances with the user requested services and provide the user with information related to available cloud appliances that meet the user's request.

Abstract: Embodiments relate to systems and methods for a cross-vendor mapping service in cloud networks. A mapping service can be provided external to one or more sets of clouds which can access vendor databases in those clouds, and generate reports on software compatibility for software resources available in those diverse cloud networks. A user in an original cloud may wish to construct an image of a set of appliances or other services or entities in a second, external cloud or clouds. The external target cloud(s) may have different application sets, and/or applications available from different vendors, than those software resources hosted in the original cloud. A mapping service external to the participating clouds can enumerate the applications or other resources available in an external cloud, and generate a mapping or translation of those components to construct desired appliance images in that destination. Subscription terms can also be translated between clouds.

Abstract: A decision system for providing customized deployment architectures to users of a cloud computing environment. The decision system can identify one or more parameters for analyzing applications and processes running in a cloud, monitor the applications and processes executed in the cloud, and collect information such as usage of cloud resources, number and type of computing processes instantiated, software programs utilized by the computing processes. The decision system can then generate customized deployment architectures based on the collected information.

Abstract: A decision system for providing ranked candidate cloud computing environments to customers for migration of subscribed services. The decision system can receive user usage history data and compare parameters of subscribed services on a host cloud to candidate clouds. Based on the comparison, a rank of candidate clouds for migration of the subscribed services can be determined and supplied to the customer.

Abstract: A decision system for providing ranked candidate cloud computing environments to customers for migration of subscribed services. The decision system can receive user usage history data and compare parameters of subscribed services on a host cloud to candidate clouds. Based on the comparison, a rank of candidate clouds for migration of the subscribed services can be determined and supplied to the customer.

Abstract: Embodiments relate to systems and methods for reclassifying a set of virtual machines in a cloud-based network. The systems and methods can analyze virtual machine data to determine performance metrics associated with the set of virtual machines, as well as target data to determine a set of target machines to which the set of virtual machines can be reassigned or reclassified. In embodiments, benefits of reassigning any of the set of virtual machines to any of the set of target virtual machines can be determined. Based on the benefits, the systems and methods can reassign or reclassify appropriate virtual machines to appropriate target virtual machines.

Abstract: Embodiments relate to systems and methods for brokering optimized resource supply costs in a host cloud-based network using predictive workloads. In aspects, a set of usage histories can store patterns for users in a host cloud-based network recording the consumption of processor, memory, storage, operating system, application, or other resources subscribed to by the user. The operator of the cloud management system hosting the workloads of one or more users can track the aggregate user histories reflecting those workloads, and analyze them in terms of different time periods over which demands for resources may intensity or relax. The cloud management system can examine those workload patterns, and generate a set of predictively re-assigned workloads to be supported by different sets of resource servers during offpeak and/or other periods.

Abstract: Embodiments relate to systems and methods for identifying usage histories for producing optimized utilization in a cloud-based network. In particular, a target cloud can receive usage histories corresponding to end user usage in a respective set of other clouds. In embodiments, the target cloud can simulate an execution of the usage histories on resources in the target cloud to generate a set of utilization ratios. Further, the target cloud can determine a desirable usage history from the set of utilization ratios based on highly optimized resource usage within the target cloud. In embodiments, an administrator of the target cloud can provide a deployment recommendation to an administrator of the cloud associated with the desirable usage history.

Abstract: Embodiments relate to systems and methods for combinatorial optimization of multiple resources across a set of cloud-based networks. In aspects, a set of usage histories can store patterns for users in a host cloud-based network recording the consumption of processor, memory, storage, operating system, application, or other resources subscribed to by the user. The user can be a corporation or other collective user. A deployment engine can identify similar target resources available in a set of target clouds. The engine can receive selection criteria for selecting target clouds for a migration of the user's deployment. In the combinatorial selection, each target cloud can independently supply one or more target resources. The engine can thus identify a series of combinations of target resources and target clouds supplying those resources to discover combinations of target clouds and target resources that can satisfy or optimize the selection criteria, such as cost or others.